Immunoassay direct for 3-amino-5-morpholinomethyl-2-oxazolidone (AMOZ), the metabolite of furaltadone, based on a specific antibody was usually unavailable due to its small molecule weight. In this ...work, a hapten with a double bond and an active carboxyl group was designed and then conjugated to peptide dendrimer to obtain novel multiple haptens. The haptens and multiple haptens were coupled to bovine serum albumin as immunogens. Polyclonal antibodies showed binding to free AMOZ in a heterologous competitive indirect enzyme-linked immunosorbent assay were obtained. The assay showed IC
50
(half maximal inhibitory concentration) of 4.1 μg/kg and limit of detection of 0.2 μg/kg for AMOZ. Recoveries of AMOZ from grass carp were tested from 83.1% to 117.0%, with the coefficient of variation below 12%. As no laborious derivatisation procedure was employed, the proposed assay should be useful for the screening of AMOZ for a large number of samples.
Nanobodies have several advantages, including great stability, sensibility, and ease of production; therefore, they have become important tools in immunoassays for chemical contaminants. In this ...manuscript, nanobodies for the detection of the toxin Nodularin-r (NOD-R), a secondary metabolite of cyanobacteria that could cause a safety risk for drinks and food for its strong hepatotoxicity, were for the first time selected from an immunized Bactrian camel VHH phage display library. Then, a sensitive indirect competitive enzyme-linked immunosorbent assay (ic-ELISA) for NOD-R, based on the nanobody N56 with great thermostability and organic solvent tolerance, was established under optimized conditions. The results showed that the limit of detection for NOD-R was 0.67 µg/L, and the average spike recovery rate was between 84.0 and 118.3%. Moreover, the ic-ELISA method was validated with spiked water sample and confirmed by UPLC–MS/MS, which indicated that the ic-ELISA established in this work is a reproducible detection assay for nodularin residues in water samples.
Microcystins, the lethal cyanotoxins from Microcystis aeruginosa, can inhibit the activity of protein phosphatase and promote liver tumors. Herein, a dual-modal split-type immunosensor was ...constructed to detect microcystin-LR (MC-LR), based on the photocurrent change of CdS/ZnO hollow nanorod arrays (HNRs) and the blue shift of the surface plasmon resonance peak from Au nanobipyramids@Ag. By using mesoporous silica nanospheres as the carrier to immobilize secondary antibody and DNA primer, a hybridization chain reaction was adopted to capture alkaline phosphatase, while its catalytic reaction product, ascorbic acid, exhibited dual functions. The detailed mechanism was investigated, showing that ascorbic acid can not only act as the electron donor to capture the holes in CdS/ZnO-HNRs, leading to the increase photocurrent, but also as the reductant to form silver shells on Au nanobipyramids, generating multiply vivid color variations and blue shifts. Compared with the traditional photoelectrochemical immunosensor or colorimetric method for MC-LR, a more accurate and reliable result can be obtained, due to different mechanisms and independent signal transduction. Therefore, this work can not only propose a new dual-modal immunosensor for MC-LR detection but also provide innovative inspiration for constructing sensitive, accurate, and visual analysis for toxins.
An indirect competitive enzyme-linked immunosorbent assay (icELISA) with enhanced specificity for melamine in milk was developed. Three haptens of melamine with different spacer-arms were used to ...prepare different plate coating antigens. It was found that the icELISA show best sensitivity and specificity to melamine when using the coating antigen prepared by coupling 3-(4,6-diamino-1,6-dihydro-1,3,5-triazin-2-ylthio)propanoic acid (Hapten C) with ovalbumin (OVA). The 50% inhibitory concentration (IC50) value was 35.4 ng·mL−1, the limit of detection (LOD) was 8.9 ng·mL−1 and the detectable working range (20–80% inhibitory concentration) was from 14.9 to 108.5 ng·mL−1, respectively. Compared to the ELISA results previously reported, the developed icELISA in the present study showed a much lower cross-reactivity to cyromazine, a fly-killing insecticide widely used in vegetables and stables. Recoveries obtained from milk samples in this study were in agreement with those obtained using the HPLC-MS method, indicating the detection performance of the icELISA could meet the requirement of the residue limit set by the Codex Alimentarius Commission. Therefore, the developed immunoassay can be applied for the analysis of melamine presented in milk.
•A hybrid model for monitoring a project with a GERT-type network is proposed.•The EDM analysis for a project with the GERT-type network is conducted.•The synergistic effect of multiple control ...points is considered.•Several regression algorithms are utilized to estimate project duration.
Project monitoring is an important topic in the field of project management. This paper proposed a hybrid model of stochastic EDM (Earned Duration Management) and machine learning for a complex project with a GERT-type (Graphical Evaluation Review Technique) network. First, an EDM analysis for a GERT-type network is conducted based on the Monte Carlo simulation. Then, considering the synergistic effect of multiple control points, a new project monitoring algorithm is designed to identify deviations and generate early warning signals. Consequently, several regression algorithms are utilized to estimate the expected project completion time. Besides, the effect of different control points, different project due dates and machine learning algorithms on model performance is explored. An illustrative case study is used to demonstrate the effectiveness of the proposed model.
highlights•An emergency logistics model for relief logistics planning in post-disaster stage is proposed.•A robust optimization approach is adopted to cope with uncertainties in demand and ...transportation time.•A numerical example is utilized to investigate the application of the proposed model.•Sensitivity analyses explore the trade-off between optimization and robustness.•The robustness of the solutions generated by the robust model is assessed by comparing with the deterministic model.
Emergency logistics is an essential component of post-disaster relief campaigns. However, there are always various uncertainties when making decisions related to planning and implementing post-disaster relief logistics. Considering the particular environmental conditions during post-disaster relief after a catastrophic earthquake in a mountainous area, this paper proposes a stochastic model for post-disaster relief logistics to guide the tactical design for mobilizing relief supply levels, planning initial helicopter deployments, and creating transportation plans within the disaster region, given the uncertainties in demand and transportation time. We then introduce a robust optimization approach to cope with these uncertainties and deduce the robust counterpart of the proposed stochastic model. A numerical example based on disaster logistics during the Great Sichuan Earthquake demonstrates that the model can help post-disaster managers to determine the initial deployments of emergency resources. Sensitivity analyses explore the trade-off between optimization and robustness by varying the robust optimization parameter values.
In this study, a smartphone-based quantitative dual detection mode device, integrated with gold nanoparticles (GNPs) and time-resolved fluorescence microspheres (TRFMs) lateral flow immunoassays ...(LFIA) for multiplex mycotoxins in cereals were established. The most frequently used visible light and fluorescence detection modes were integrated in one device. A user-friendly application was self-written to rapidly quantify results. GNPs-LFIA and TRFMs-LFIA were used to detect aflatoxin B1 (AFB1), zearalenone (ZEN), deoxynivalenol (DON), T-2 toxin (T-2), and fumonisin B1 (FB1). The visible limits of detection (vLODs) were 10/2.5/1.0/10/0.5, 2.5/0.5/0.5/2.5/0.5 μg/kg for the two methods, respectively. The quantitative limits of detection (qLODs) were 0.59/0.24/0.32/0.9/0.27, 0.42/0.10/0.05/0.75/0.04 μg/kg, respectively. The recoveries of both LFIAs ranged from 84.0%-110.0%. A parallel analysis in 30 naturally contaminated cereal samples was conducted by liquid chromatography–tandem mass spectrometry (LC-MS/MS), the results showed good consistency, indicating the practical reliability of the established methods. The developed two smartphone-based LFIAs provide a promising technique for multiplex, highly sensitive, and on-site detection of mycotoxins.
•GNP and TRFMs-LFIAs were developed to detect co-contamination of 20 mycotoxins from five classes.•A portable reading platform developed based on smartphone App has the advantage of universal data analysis.•Visible light and fluorescence detection modes are integrated in one device.
In recent years, the frequent economically motivated adulteration (EMA) caused by component displacement, illegal addition, and other problems makes the food authenticity become a global issue, which ...requires appropriate identification methods. Raman spectroscopy combination with chemometrics becomes a rapid, non-destructive method to verify the nature or origin of food. This review assembles and comprehensively summarizes the principle, workflow, advantages, challenges and applications of Raman spectroscopy in food authenticity. Besides, existing problems and outlooking on Raman spectroscopy are also discussed.
•This work emphasized the Raman spectrum information processing in food authentication.•Various chemometrics methods to enhance the accuracy of Raman spectral modeling were systematically discussed.•Plenty of strategies for Raman spectroscopy application to specific food authenticity were comrehensively reviewed.•This work will be valuable to the deep research about food authentication.
OBJECTIVE： To investigate the neural differentiation capacity of water extraction of velvet antler.METHODS： Velvet antler（Cervus Nippon Temminck） polypeptide（VAP） was used to differentiate neural ...stem cells（NSCs） towards neurons in the study. Firstly, we obtain the polypeptides of VAP by water extraction. Secondly, we observed the morphology, assayed the factors in the media by enzyme-linked immunosorbent assay, and detected the special neural molecules by immuno fl uorescence staining. NSCs were cultured on the cell climbing film. After neuronal differentiation, differentiated NSCs were mounted for immunocytochemistry with immunofluorescence technique.RESULTS： The differentiating cells look like neuron,some special factors, such as Glial cell line-derived neurotrophic factor, nerve growth factor, in the media can be detected while differentiated neuron-like cells can express the special neural molecules.CONCLUSION： Differentiation of NSCs towards neurons can be induced by velvet antler polypeptide.
•A post-disaster relief distribution model for commodities and injured people is proposed.•A robust optimization approach is adopted to cope with uncertainties in demand and supply.•A model ...predictive control approach is utilized to adjust existing plan accordance with updated information.•A numerical example is utilized to investigate the application of the proposed model and approach.
Emergency distribution is an important aspect of disaster response. However, when planning such activities, decision makers should consider not only uncertain and dynamic input data such as supply and demand, but also the real-time adjustment requirements of the existing distribution plans that account for the deviation between the predicted and actual (or observed) values of the input data. Consequently, we present a multi-commodity, multi-period distribution model that considers both relief commodities and injured people to minimize the total weighted unmet demand throughout the planning horizon. Furthermore, we propose a rolling horizon-based framework, based on the robust model predictive control (RMPC) approach, to obtain robust relief distribution plans and adjust them in accordance with updated real-time information. We then use a numerical example based on the Great Wenchuan Earthquake that occurred on May 12, 2008, in Sichuan Province, China, to investigate the application of our proposed model and framework, and we perform a detailed analysis of the influence of the settings of robust optimization parameters.
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